Remove Data Management Remove Data Warehouse Remove Healthcare Remove Monitoring
article thumbnail

Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing

Astera

Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing As businesses deal with larger and more diverse volumes of data, managing that data has become increasingly difficult. These examples show the high level of flexibility and adaptability provided by data vault.

article thumbnail

The Future of AI in Data Warehousing: Trends and Predictions 

Astera

Data management can be a daunting task, requiring significant time and resources to collect, process, and analyze large volumes of information. Continuous Data Quality Monitoring According to Gartner , poor data quality cost enterprises an average of $15 million per year.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Information Marts: Enabling Agile, Scalable, and Accurate BI

Astera

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

Agile 52
article thumbnail

The Benefits of Using a Data Warehouse for Healthcare Data Management

Astera

In the world of medical services, large volumes of healthcare data are generated every day. Currently, around 30% of the world’s data is produced by the healthcare industry and this percentage is expected to reach 35% by 2025. The sheer amount of health-related data presents countless opportunities.

article thumbnail

7 Data Quality Metrics to Assess Your Data Health

Astera

Data that meets the requirements set by the organization is considered high-quality—it serves its intended purpose and helps in informed decision-making. Such a detailed dataset is maintained by trained data quality analysts, which is important for better decision-making and patient care. million annually due to low-quality data.

article thumbnail

Data Profiling: Types, Techniques and Best Practices

Astera

Types of Data Profiling Data profiling can be classified into three primary types: Structure Discovery: This process focuses on identifying the organization and metadata of data, such as tables, columns, and data types. This certifies that the data is consistent and formatted properly.

article thumbnail

Single Source of Truth: What Is It and Why Is It Essential?

Astera

In today’s data-driven world, businesses rapidly generate massive amounts of data. Managing this data effectively and timely is critical for decision-making, but how can they make sense of all this data most efficiently? Everyone with the same access level can access the same data to work with.